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8 repositorios

Awesome GitHub RepositoriesLayout Preservation

Capabilities for extracting text while maintaining the original visual spatial arrangement.

Distinct from Text Extraction: Distinct from general Text Extraction by specifically focusing on preserving the visual coordinates and spacing of the layout.

Explore 8 awesome GitHub repositories matching data & databases · Layout Preservation. Refine with filters or upvote what's useful.

Awesome Layout Preservation GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • run-llama/liteparseAvatar de run-llama

    run-llama/liteparse

    10,782Ver en GitHub↗

    A fast, helpful, and open-source document parser

    Extracts text, tables, and images from PDFs and office documents while preserving spatial layout and structure.

    Rustdocument-ocrdocument-processingocr
    Ver en GitHub↗10,782
  • py-pdf/pypdfAvatar de py-pdf

    py-pdf/pypdf

    9,818Ver en GitHub↗

    pypdf is a Python library for parsing, manipulating, and generating PDF documents. It provides high-level operations for document processing, such as merging multiple files into one or splitting a single document into smaller files. The project includes specialized tools for managing interactive elements, including the creation and modification of annotations, hyperlinks, and form fields. It also supports advanced metadata management, allowing for the extraction and modification of standard document properties and XML-based XMP metadata. Beyond basic structural changes, the library covers pa

    Retrieves text while preserving the visual layout, orientation, and spacing of the original document.

    Pythonhelp-wantedpdfpdf-documents
    Ver en GitHub↗9,818
  • ripperhe/bobAvatar de ripperhe

    ripperhe/Bob

    9,693Ver en GitHub↗

    Bob is an extensible macOS utility designed for screen text extraction, translation aggregation, and speech synthesis. It functions as a wrapper that integrates multiple optical character recognition and translation services into a single interface, allowing users to capture screen areas, decode QR codes, and convert visual text into editable strings. The tool distinguishes itself through a plugin-based architecture that supports the integration of custom translation, speech synthesis, and image recognition APIs. It enables multi-engine parallel execution, allowing a single request to be proc

    Uses coordinate-based algorithms to maintain paragraph structures and formatting when extracting text from images.

    bobappchatgptdeepseek
    Ver en GitHub↗9,693
  • jsvine/pdfplumberAvatar de jsvine

    jsvine/pdfplumber

    9,732Ver en GitHub↗

    pdfplumber is a PDF data extraction library and layout analysis tool used to retrieve text, tables, and geometric objects from PDF files using precise coordinate-based analysis. It functions as a layout analyzer and table parser that identifies the bounding boxes and visual coordinates for every character and image on a page. The library distinguishes itself through visual debugging capabilities, allowing users to render PDF pages as images and draw annotations to verify the position of extracted data. It employs line and intersection analysis to identify cell structures and convert unstructu

    Converts characters into strings or word lists while preserving visual arrangement and reading direction.

    Pythonpdfpdf-parsingtable-extraction
    Ver en GitHub↗9,732
  • pymupdf/pymupdfAvatar de pymupdf

    pymupdf/PyMuPDF

    9,086Ver en GitHub↗

    PyMuPDF is a comprehensive PDF manipulation library and document analysis tool. It serves as a text extraction tool, OCR engine, and image converter, providing a programmatic interface to edit, merge, split, and optimize PDF and Office documents. The project distinguishes itself through high-performance capabilities, including the use of C-bindings for low-level manipulation and parallelized page processing to accelerate workloads. It provides specialized conversion paths, such as transforming PDF content into Markdown for retrieval-augmented generation and large language model pipelines. It

    Extracts text while precisely preserving the original visual spatial arrangement and coordinates of the content.

    Pythondata-scienceepubextract-data
    Ver en GitHub↗9,086
  • funstory-ai/babeldocAvatar de funstory-ai

    funstory-ai/BabelDOC

    7,752Ver en GitHub↗

    BabelDOC is a technical document translation system designed to translate PDF files while preserving their original layout and styling. It functions as a layout-preserving translator that utilizes large language models to convert content into target languages, specifically tailored for scientific and technical documents. The system distinguishes itself through specialized handling of academic content, including the identification and preservation of mathematical formulas and complex layout structures. It ensures technical accuracy by employing glossary-driven terminology enforcement, using so

    Extracts text from PDFs and reflows translated content back into original spatial bounding boxes.

    Python
    Ver en GitHub↗7,752
  • reinderien/mimicAvatar de reinderien

    reinderien/mimic

    3,755Ver en GitHub↗

    Mimic is a unicode homoglyph generator and text obfuscation tool. It functions as a character substitutor that replaces standard ASCII characters with visually similar Unicode symbols to create text that appears correct to humans but is functionally different. The project is used for source code obfuscation by inserting subtle syntax errors into code to hide intent or break automated analysis. It also serves as a tool for textual adversarial testing to evaluate the resilience of software filters against maliciously crafted input. The utility achieves these results through a mapping system th

    Maintains the original visual spatial arrangement and length of the source text during character replacement.

    Python
    Ver en GitHub↗3,755
  • robertknight/ocrsAvatar de robertknight

    robertknight/ocrs

    1,843Ver en GitHub↗

    Este proyecto es un motor de reconocimiento óptico de caracteres (OCR) basado en terminal que utiliza modelos de redes neuronales para extraer texto y datos de diseño espacial de imágenes. Funciona tanto como una utilidad de línea de comandos para el procesamiento automatizado de texto como una biblioteca para integrar el reconocimiento basado en machine learning en flujos de trabajo más amplios. El motor se distingue por una tubería de procesamiento modular que admite la carga de modelos personalizados y la inicialización de pesos mapeados en memoria para una ejecución eficiente. Preserva la estructura del documento mediante el seguimiento de coordenadas geométricas precisas para cada elemento de texto detectado, y permite el refinamiento de la salida a través de reglas de validación a nivel de carácter. El sistema incluye herramientas integrales para la ingesta de imágenes, incluyendo la captura directa desde portapapeles del sistema y contenido del navegador. Proporciona capacidades de diagnóstico mediante la generación de superposiciones visuales y artefactos de procesamiento intermedio para verificar la precisión del reconocimiento y solucionar problemas de rendimiento de la tubería. El software se distribuye como un binario estático para asegurar la portabilidad entre entornos sin requerir dependencias externas.

    Exports extracted text and spatial coordinates to preserve the original document structure.

    Rustcomputer-visionmachine-learningocr
    Ver en GitHub↗1,843
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  3. Text Processing Utilities
  4. Text Extraction
  5. Layout Preservation